Sequencing yeast lines to measure rates of neutral and deleterious mutations

对酵母系进行测序以测量中性和有害突变率

• 批准号: 8337747
• 负责人: Dmitri Petrov
• 金额: $ 56.98万
• 依托单位: NEW YORK UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-30 至 2015-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8337747
• 关键词: Affect; Biological Assay; Cell division; Cells; Collection; Communities; Complex; DNA; DNA Repair; DNA Sequence; DNA biosynthesis; Data; Development; Diploidy; Evolution; Future; Generations; Genetic; Genetic Polymorphism; Genetic Variation; Genome; Genomic Instability; Genomics; Genotype; Growth; Haploidy; Inbreeding; Individual; Investigation; Laboratories; Link; Mating Types; Measurement; Measures; Mutation; Mutation Spectra; Natural Selections; Pattern; Population; Population Sizes; Process; Quantitative Genetics; Research; Resources; Saccharomyces cerevisiae; Site; Systems Biology; Technology; Theoretical model; Variant; Yeasts; asexual; base; experience; fitness; genetic analysis; genetic resource; genome sequencing; high throughput screening; human disease; next generation; prevent; purge; research study; sex; trait

DESCRIPTION (provided by applicant): Spontaneous mutations are the ultimate cause of genetic differences between individuals, and are therefore key to understanding the evolutionary process and many human diseases. However, the rates and patterns of mutation are difficult to measure because mutations are rare and are immediately subjected to natural selection. Recent advances in DNA sequencing technology, combined with the development of high- throughput assays of components of fitness, such as growth rate, present a unique opportunity to obtain a dramatically more precise and comprehensive view of the spectrum of spontaneous mutations. Mutation rates and patterns can be measured directly using mutation-accumulation (MA) lines, which are constructed in the laboratory by many generations of repeated population bottlenecking. The bottlenecks keep effective population size low and therefore prevent natural selection from purging deleterious mutations. In this project, a collection of 149 diploid MA lines of the genetically well-characterized yeast species, Saccharomyces cerevisiae, will be used. The lines were passaged for 2100 generations and therefore collectively capture over 300,000 cell divisions (600,000 replications of a haploid genome). Haploids have been used previously to estimate mutational spectra in yeast, but diploidy has several critical advantages, including better shielding of deleterious mutations, avoidance of genomic instability, and facilitation of downstream genetic analyses. In Aim 1, the complete genome sequences of all 149 MA lines and their common ancestral line will be obtained using next-generation (Illumina) technology. This will yield almost two orders of magnitude more direct data on spontaneous mutations than previously achieved. In Aim 2, genetic analysis will be performed to identify each diploid MA line that carries a highly deleterious mutation. For each such line, high-coverage sequencing of pooled haploid progeny will identify the highly deleterious mutation molecularly. In Aim 3, high-throughput growth-rate assays will be performed on haploid progeny from each diploid MA line. The growth-rate assays will provide an estimate of the distribution of marginal fitness effects of spontaneous mutations. This will be a major advance because the rate of deleterious mutations is typically inaccessible to direct measurement, yet is a fundamental parameter in theoretical models of evolution. Moderately deleterious mutations will be identified molecularly by high-coverage sequencing of pooled haploid progeny. In Aim 4, a collection of 96 haploid lines of mating-type a, each derived from a different diploid MA line, will be established, as a community resource for studying the effects of mutations on complex traits. The complete genotype of each line will be obtained by sequencing. For maximum utility, two sets of lines derived from these 96 lines will also be made: haploids of mating-type a and homozygous a/a diploids. This project will have an immediate and major impact on research in quantitative genetics, systems biology and evolutionary genetics and genomics, by accelerating future investigations of the links between mutations and their phenotypic effects.

自发突变是个体间遗传差异的最终原因，因此是理解进化过程和许多人类疾病的关键。然而，突变的速率和模式很难测量，因为突变是罕见的，并立即受到自然选择。DNA测序技术的最新进展，结合适合度组分（如生长速率）的高通量测定的发展，提供了获得自发突变谱的显著更精确和全面的视图的独特机会。突变率和突变模式可以直接使用突变积累（MA）系来测量，MA系是在实验室中通过多代重复的群体验证构建的。瓶颈使有效种群规模保持在较低水平，从而阻止自然选择清除有害突变。在这个项目中，收集了149个二倍体MA系的遗传特征良好的酵母物种，酿酒酵母，将被使用。这些细胞系传代2100代，因此总共捕获超过300，000次细胞分裂（600，000次单倍体基因组复制）。单倍体先前已被用于估计酵母中的突变谱，但二倍体具有几个关键优势，包括更好地屏蔽有害突变，避免基因组不稳定性，以及促进下游遗传分析。在目标1中，将使用下一代（Illumina）技术获得所有149个MA系及其共同祖先系的完整基因组序列。这将产生几乎两个数量级以上的自发突变的直接数据比以前实现。在目标2中，将进行遗传分析以鉴定携带高度有害突变的每个二倍体MA系。对于每一个这样的系，合并的单倍体后代的高覆盖测序将在分子上鉴定高度有害的突变。在目标3中，将对来自每个二倍体MA系的单倍体后代进行高通量生长速率试验。生长率测定将提供自发突变的边际适应性效应分布的估计。这将是一个重大的进步，因为有害突变的速率通常无法直接测量，但却是进化理论模型中的一个基本参数。中度有害突变将通过合并的单倍体后代的高覆盖测序在分子上鉴定。在目标4中，将建立96个交配型a的单倍体系的集合，每个系来自不同的二倍体MA系，作为研究突变对复杂性状的影响的社区资源。将通过测序获得各品系的完整基因型。为了获得最大的效用，还将从这96个品系中获得两组品系：交配型a的单倍体和纯合a/a二倍体。该项目将通过加速未来对突变及其表型效应之间联系的研究，对定量遗传学、系统生物学和进化遗传学和基因组学的研究产生直接和重大的影响。